You recently submitted your first manuscript for publication, and you were pleased when the editor decided to send the manuscript out for peer review. Now you have gotten the reviews back, and the editor has asked you to revise your manuscript in light of the reviewers' comments. How should you tackle this task?

The comprehensive guide by \citet{Noble_2017} "Ten simple rules for writing a response to reviewers" gives you some concrete tips to organize and write a compelling letter for reviewers addressing their comments.

Rule 6 states:

Use typography to help the reviewer navigate your response:

Use changes of typeface, color, and indenting to discriminate between 3 different elements: the review itself, your responses to the review, and changes that you have made to the manuscript.

If you are writing your manuscript in Authorea, you can now very easily produce a changelog of your manuscript (the changes you have made to the manuscript) which you can export as PDF and include in your response to reviewers.

This document shows the required format and appearance of a manuscript prepared for SPIE journals. It is prepared using LaTeX2e with the class file spieman.cls. The abstract should consist of a single paragraph containing no more than 200 words. It should be a summary of the paper and not an introduction. Because the abstract may be used in abstracting and indexing databases, it should be self-contained (that is, no numerical references) and substantive in nature, presenting concisely the objectives, methodology used, results obtained, and their significance. A list of up to eight keywords should immediately follow, with the keywords separated by commas and ending with a period. The body of the manuscript should be double-spaced and fully justified.

If you run a company or a website, cohort analysis is a great way to understand engagement and retention of your users. For example, how many of your users who signed up in June went back to your site in July? The chart below, for example, shows that 33.36% of all users who signed up on Month 0, came back to the site on Month 1. Google Analytics recently added cohort analysis to the set of metrics that they offer to their users, so that you can generate retention curves like the one below on the fly. It is still in Beta, but it allows you to understand user retention over time, especially if you use Google Analytics with User ID view, that is: you track data of signed up users with accounts.

A new eraFall marks a new era for Authorea. Summer was already very eventful -- 8,200+ custom journal templates, increased rendering speed, dictionary support for new languages, improved article metadata, better import and export functionality, and many more improvements (see our product roadmap). Fall is going to be even more eventful! We are launching a modern design and an improved rich-text editor! Our editor "rewrite" marks the culmination of months of work and it is the biggest project we've undertaken since founding Authorea. We hope you'll like it.We'll be rolling out the new Editor to all our users over the next few weeks after our private beta test. You'll get a message very soon with a link to opt-in. Here are some of the updates we think you’ll find exciting:A modern new lookIt took a long time but we finally have a dashing new look: familiar and easy to use like most modern word processors, and at the same time perfectly tailored for the writing needs of researchers. And this is just the beginning. We will continue improving your reading and writing experience.

Preamble

A variety of research on human cognition demonstrates that humans learn and communicate best when more than one processing system (e.g. visual, auditory, touch) is used. And, related research also shows that, no matter how technical the material, most humans also retain and process information best when they can put a narrative "story" to it. So, when considering the future of scholarly communication, we should be careful not to do blithely away with the linear narrative format that articles and books have followed for centuries: instead, we should enrich it.

Much more than text is used to communicate in Science. Figures, which include images, diagrams, graphs, charts, and more, have enriched scholarly articles since the time of Galileo, and ever-growing volumes of data underpin most scientific papers. When scientists communicate face-to-face, as in talks or small discussions, these figures are often the focus of the conversation. In the best discussions, scientists have the ability to manipulate the figures, and to access underlying data, in real-time, so as to test out various what-if scenarios, and to explain findings more clearly. This short article explains—and shows with demonstrations—how scholarly "papers" can morph into long-lasting rich records of scientific discourse, enriched with deep data and code linkages, interactive figures, audio, video, and commenting.

Recent asteroseismic analyses have revealed the presence of strong (B≳10⁵ G) magnetic fields in the cores of many red giant stars. Here, we examine the implications of these results for the evolution of stellar magnetic fields, and we make predictions for future observations. Those stars with suppressed dipole modes indicative of strong core fields should exhibit moderate but detectable quadrupole mode suppression. The long magnetic diffusion times within stellar cores ensure that dynamo-generated fields are confined to mass coordinates within the main sequence convective core, and the sharp increase in dipole mode suppression rates above 1.5 M⊙ may be explained by the larger convective core masses and faster rotation of these more massive stars. In clump stars, core fields of $\sim 10^5 \, {\rm G}$ can suppress dipole modes, whose visibility should be equal to or less than the visibility of suppressed modes in ascending red giants. High dipole mode suppression rates in low-mass (M ≲ 2 M⊙) clump stars would indicate that magnetic fields generated during the main sequence can withstand subsequent convective phases and survive into the compact remnant phase. Finally, we discuss implications for observed magnetic fields in white dwarfs and neutron stars, as well as the effects of magnetic fields in various types of pulsating stars.

Asteroseismology of 1.0 − 2.0M⊙ red giants by the _Kepler_ satellite has enabled the first definitive measurements of interior rotation in both first ascent red giant branch (RGB) stars and those on the Helium burning clump. The inferred rotation rates are 10 − 30 days for the ≈0.2M⊙ He degenerate cores on the RGB and 30 − 100 days for the He burning core in a clump star. Using the MESA code we calculate state-of-the-art stellar evolution models of low mass rotating stars from the zero-age main sequence to the cooling white dwarf (WD) stage. We include transport of angular momentum due to rotationally induced instabilities and circulations, as well as magnetic fields in radiative zones (generated by the Tayler-Spruit dynamo). We find that all models fail to predict core rotation as slow as observed on the RGB and during core He burning, implying that an unmodeled angular momentum transport process must be operating on the early RGB of low mass stars. Later evolution of the star from the He burning clump to the cooling WD phase appears to be at nearly constant core angular momentum. We also incorporate the adiabatic pulsation code, ADIPLS, to explicitly highlight this shortfall when applied to a specific _Kepler_ asteroseismic target, KIC8366239.

_This is the author’s version of the work. It is posted here for personal use, not for redistribution. The definitive version was published in Nature on 04 January 2016, DOI:10.1038/nature16171_ Magnetic fields play a role in almost all stages of stellar evolution . Most low-mass stars, including the Sun, show surface fields that are generated by dynamo processes in their convective envelopes . Intermediate-mass stars do not have deep convective envelopes , although 10% exhibit strong surface fields that are presumed to be residuals from the stellar formation process . These stars do have convective cores that might produce internal magnetic fields , and these might even survive into later stages of stellar evolution, but information has been limited by our inability to measure the fields below the stellar surface . Here we use asteroseismology to study the occurrence of strong magnetic fields in the cores of low- and intermediate-mass stars. We have measured the strength of dipolar oscillation modes, which can be suppressed by a strong magnetic field in the core , in over 3,600 red giant stars observed by . About 20% of our sample show mode suppression but this fraction is a strong function of mass. Strong core fields only occur in red giants above 1.1 solar masses (1.1), and the occurrence rate is at least 60% for intermediate-mass stars (1.6–2.0), indicating that powerful dynamos were very common in the convective cores of these stars.